Browsing by Subject "Cost control."

Now showing 1 - 8 of 8

Open Access
Algorithms for 2 edge connectivity with fixed costs in telecommunications networks
(2011) Güzel, Umut
In this thesis, several algorithms are developed in order to provide costeffective and survivable communication in telecommunications networks. In its broadest sense, a survivable network is one which can maintain communication even in the presence of a physical breakdown. There are several ways of providing survivable communication in a given network. Our choice is to hedge against single link failures and provide two edge disjoint paths for every source and destination pair. Each edge in the network is assumed to have a variable unit routing cost and a fixed usage cost. Our objective is the minimization of the total routing cost of the traffic demand and the fixed cost of the utilized links. Several constructive and improvement type heuristics are developed and tested extensively in an experimental design setting.
Open Access
An application of Silver Meal Heuristic to MRP lot sizing decisions at Turk Traktor Fabrikasi
(1995) Esmer, Berkhan N.
MRP does not consider setup and inventory holding costs for lot sizing but very quick algorithms like Silver-Meal can be used for lot sizing decisions. A module to apply Silver-Meal Heuristic to manufacturing work order releases at Türk Traktör Fabrikasy, Ankara, Turkey is designed and tested for 3 months. The module processes demand for finished goods, determines lot sizes, checks capacities by loading machines according to the schedule and reports the setup, inventory holding and overtime costs. These cost figures are compared with the MRP lot sizes. It is observed that, the planning time decreased by 90% by designing module in PCs connected to the main databases, and the total costs decreased by 50%.
Open Access
Capital's response to globalization : "a comparative analysis of the adjustment patterns of mark-ups in post-liberalization developing countries"
(2004) Buturak, Gökhan
In this thesis, I investigate the capital’s response to the new world economic order termed as “globalization”. It is asserted in many theoretical and popular writings that increased pressures of global competition would squeeze the profit margins and reduce capital returns. I discuss this proposition theoretically and then test for it using manufacturing data for a selected group of developing countries under post-liberalization. I utilize time series and panel data econometrics to study the behavior of markups (gross profit margins) against wage costs, trade openness, and investment share in the GDP as a proxy for capacity utilization. Contrary to expectations, I find no significant conclusive evidence on the sign of “openness” on profit margins in many countries of my sample. My results also reveal that though mark-ups are negatively related with real wage costs in most of the Latin American countries in my sample, they have a positive and statistically significant relation to real wage costs in Turkish manufacturing. Finally, investment shares and mark-ups reveal a negative relationship for Argentina and Turkey and a positive one for Colombia.
Open Access
A dynamic pricing policy for perishables with stochastic demand
(2001) Yıldırım, Gonca
III this study, we consider the pricing of perishables in an inventory system where items have a fixi'd lifetime. Unit demands come from a Poisson Process with a price-dependent rate. The instances at which an item is withdrawn from inventory due to demand constitute decision epochs for setting the sales price; the time elapsed between two such consecutive instances is called a period. The sales price at each decision epoch is taken to be a lunction of Tj denoting the remaining lifetime when tin' inventory level drops to z, i = 1,...,Q. The objective is to determine the optimal pricing policy (under the proposed class) and the optimal initial stocking level to maximize the discounted expected profit. A Dynamic Programming approach is used the solve the problem numerically. Using the backward recursion, the optimal price paths are determined for the discounted expected profit for various combinations of remaining lifetimes. Our numerical studies indicate that a single price policy results in significantly lower profits when compared with our formulation.
Open Access
An inventory model for randomly perishing goods
(2000) Yüksel, Banu
In this study, we consider an (s, S) ordering policy with backordering for a continuous review inventory system, where the items have a random shelflife. Assuming zero lead time and no decay until the shelflife, we derive the exact expressions for both unit and random batch demand cases with renewal demand arrivals. We present some analytical results on the cost rate function for unit demand case. A detailed numerical analysis is also provided to investigate the performance of the model which incorporates the random shelflife and comparisons with flxed shelflife are given.
Open Access
Maintenance and marginal cost analysis of a two-unit cold standby system
(1997) Hamdaoui, Chokri
The Marginal Cost Analysis (MCA) of maintenance policies is a concept gaining interest in the recent years. This approach, due to Berg, has been categorized as an Economics Oriented Approach, as different from the classical probability centered approach. The MCA has been successfully applied to the Age Replacement and the Block Replacement policies, and was shown to be flexible enough to permit extensions and generalizations. In this thesis, we apply the MCA approach to a more complex model. We consider a two-unit cold standby system. Upon failure of the working unit in the time interval [0,T) the unit is replaced by the standby unit if available. If the standby unit is in repair, the system is down, and a downtime cost is incurred. The item inspected at time T is in one of two states: “good” , or “critical” . The good unit continues operation, whereas a unit in critical state is sent to repair. The switchover is immediate. We derive and compare the marginal cost function as well as the long-run cost per unit time function.
Open Access
Order quantity and pricing decisions in linear cost inventory systems
(1992) Polatoglu, Lutfi Hakan
The primary concern of this study is to reveal the fundamental characteristics of the linear cost inventory model where price is a decision variable in addition to procurement quantity. In this context, the optimal solution must not only strike a balance between leftovers and shortages, but also simultaneously search for the best pricing alternative within the low price high demand and high price low demand tradeoff. To some extent, this problem has been studied in the literature. However, it seems that, there is a need to improve the model in order to understand the decision process better. To this end, optimal decisions must be characterised under a more general problem setting than it has been assumed in the existing models. In this study, we employ such a general model. The overall decision problem can be formulated under a dynamic programming structure. It follows that, the single period model is the basis of this periodic decision model. For this reason, we concentrate first on this problem. Having characterised the optimal solution to this basic model we extend the decision model to account for the multi-period setting. It is established with the results of this study that the decision problem in question is understood better. It is found that the characteristics of the optimal decision under the proposed model can be substantially different from the properties of the optimal solution of the corresponding classical model where there is no pricing decision. The primary reason for this is the fact that when there is a shortage in any period, the price that is set in this period could affect the future revenue which must be accounted in the overall decision problem. That is in a general model, price is an information which has an economic value that is transferred from one period to another just like transfering inventories or backlogs to future periods.
Open Access
Qualitative test-cost sensitive classification
(2008) Cebe, Mümin
Decision making is a procedure for selecting the best action among several alternatives. In many real-world problems, decision has to be taken under the circumstances in which one has to pay to acquire information. In this thesis, we propose a new framework for test-cost sensitive classification that considers the misclassification cost together with the cost of feature extraction, which arises from the effort of acquiring features. This proposed framework introduces two new concepts to test-cost sensitive learning for better modeling the real-world problems: qualitativeness and consistency. First, this framework introduces the incorporation of qualitative costs into the problem formulation. This incorporation becomes important for many real world problems, from finance to medical diagnosis, since the relation between the misclassification cost and the cost of feature extraction could be expressed only roughly and typically in terms of ordinal relations for these problems. For example, in cancer diagnosis, it could be expressed that the cost of misdiagnosis is larger than the cost of a medical test. However, in the test-cost sensitive classification literature, the misclassification cost and the cost of feature extraction are combined quantitatively to obtain a single loss/utility value, which requires expressing the relation between these costs as a precise quantitative number. Second, the proposed framework considers the consistency between the current information and the information after feature extraction to decide which features to extract. For example, it does not extract a new feature if it brings no new information but just confirms the current one; in other words, if the new feature is totally consistent with the current information. By doing so, the proposed framework could significantly decrease the cost of feature extraction, and hence, the overall cost without decreasing the classification accuracy. Such consistency behavior has not been considered in the previous test-cost sensitive literature. We conduct our experiments on three medical data sets and the results demonstrate that the proposed framework significantly decreases the feature extraction cost without decreasing the classification accuracy.